Phenotypic Phase Plane Analysis
Performs phenotypic phase plane analysis for a given metabolic model.
phpp(model, ctrlreact, rng = c(0, 0, 20, 20),
numP = 50, setToZero = TRUE, redCosts = FALSE, ...)model |
An object of class |
ctrlreact |
An object of class |
rng |
A numeric vector of length four, giving the lower and upper bounds of the
control reactions. The first two values contain the lower bounds, the last
two values the upper bounds. |
numP |
The number of points to analyse. |
setToZero |
Logical: If the mathematical programming software returns a solution status
which is not optimal, set the corresponding objective value to zero (see
also |
redCosts |
Logical: store reduced costs of the control variables. |
... |
Further arguments passed to |
The two control reactions given in argument ctrlreact are treated as
uptake reactions: reactions that transport metabolites into the metabolic
network. That means, the optimizations are performed using
abs(rng) * -1.
An object of class optsol_phpp.
Gabriel Gelius-Dietrich <geliudie@uni-duesseldorf.de>
Maintainer: Mayo Roettger <mayo.roettger@hhu.de>
Becker, S. A., Feist, A. M., Mo, M. L., Hannum, G., Palsson, B. Ø. and Herrgard, M. J. (2007) Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox. Nat Protoc 2, 727–738.
Schellenberger, J., Que, R., Fleming, R. M. T., Thiele, I., Orth, J. D., Feist, A. M., Zielinski, D. C., Bordbar, A., Lewis, N. E., Rahmanian, S., Kang, J., Hyduke, D. R. and Palsson, B. Ø. (2011) Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0. Nat Protoc 6, 1290–1307.
Edwards, J. S., Ibarra, R. U. and Palsson, B. Ø. (2001) In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data. Nat Biotechnol 19, 125–130.
Edwards, J. S., Ramakrishna, R. and Palsson, B. Ø. (2002) Characterizing the metabolic phenotype: a phenotype phase plane analysis. Biotechnol Bioeng 77, 27–36.
Bernhard Ø. Palsson (2006). Systems Biology: Properties of Reconstructed Networks. Cambridge University Press.
data(Ec_core)
# switch off glucose input
Ec_core_wo_glc <- changeUptake(Ec_core, off = "glc_D[e]")
opt <- phpp(Ec_core_wo_glc, ctrlreact = c("EX_succ(e)", "EX_o2(e)"))
# plot phenotypic phase plane
plot(opt)
# plot reduced costs of the two control reactions
plot(opt, "EX_succ(e)")
plot(opt, "EX_o2(e)")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.